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	题名	作者	年代	出处	被引量
1	评估清晨或夜晚服用降压药对24h动态血压的影响:清晨或夜间服用降压药的希腊英国联合研究显示文摘观察数据显示,临床血压水平与随后的主要不良心血管事件之间存在强烈的线性关系。然而,动态血压监测显示,夜间血压水平比24h或白天血压水平更能预测主要的不良心血管事件。此外,夜间与白天的血压比值和杓型状态也是心血管结局的重要独立预测因素。这些发现可能对抗高血压药物的最佳给药时间有影响,一些研究表明,夜晚服用降压药可能较白天服药减少心血管事件。	Poulter NR Savopoulos C Anjum A Apostolopoulou M Chapman N Cross M Falaschetti E Fotiadis S James RM Kanellos I Szigeti M Thom S Sever P Thompson D Hatzitolios AI 赵狄练桂丽	2018	中华高血压杂志2018，26，10：	7
2	显示文摘	Voltairas P A Fotiadis D I	2000	J Appl Phys2000，88，1：	1
3	Computer simu- lation of three-dimensional plaque formation and progression in the carotid artery显示文摘	Filipovic N TENG Zhong-zhao Radovic M Saveljic I Fotiadis D Parodi O	2013	Medical& Biological Engineering & Computing2013，51，6：	1
4	Flow phenomena in chemical vapor deposition of thin films 显示文摘	Jensen K F Einset E O Fotiadis D I	1991	Annual Review of Fluid Mechanics1991，23，：	1
5	An ar- rhythmia classification system based on the RR-interval signal 显示文摘	TSIPOURAS M G FOTIADIS D I SIDERIS D	2005	Artif Intell Med2005，33，3：	1
6	Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines 显示文摘	PAPADOPOULOS A FOTIADIS D I LIKAS A	2005	Artificial Intelligence in Medicine2005，34，2：	1
7	Guest Editorial Special Section on New and Emerging Technologies in Bioinformatics attd Bioengineering 显示文摘	Nikita K S Fotiadis D I	2010	I lformation Technology in Biomedicine2010，14，3：	1
8	An arrhythmia classification system based on the RR-interval signal显示文摘	Tsipouras M G Fotiadis D I	2005	Artificial Intelligence in Medicine2005，33，：	1
9	An automated method for lumen and media-adventitia border detection in a sequence of IVUS frames 显示文摘	Plissiti M E Fotiadis D I Michalis L K	2004	IEEE Transactions on Information Technology in Biomedicine2004，8，2：	1
10	The role of material parameters and mechanical stresses on magnetic and magnetostrictive hysteresis 显示文摘	Voltairas P A Fotiadis D I Massalas C V	1999	Journal of Magnetism and Magnetic Materials1999，204，12：	1
11	Artificial neural networksfor solving ordinary and partial differential equations 显示文摘	LAGARIS I E LIKAS A FOTIADIS D I	1998	IEEETransactions on Neural Networks1998，9，5：	1
12	Artificial neural networksfor solving ordinary and partial differential equations 显示文摘	LAGARIS I E LIKAS A FOTIADIS D I	1998	IEEETransactions on Neural Networks1998，9，5：	1
13	Identification of1Dand 2DPreisach models for ferromagnets and shape mem-ory alloys显示文摘	Ktena A Fotiadis D I Spanos P D	2002	International Journal of Engineering Science2002，40，：	1
14	Epileptic sei- zure detection in EEGs using time-frequency analysis 显示文摘	TZALLAS A T TSIPOURAS M G FOTIADIS D I	2009	IEEE Transactions on Information Technology in Biomedicine2009，13，5：	1
15	An automatic microcalcification detection system based on hybrid neural network classifier显示文摘	Papadopoulos A Fotiadis D I Likas A	2002	Artificial Intelligence in Medicine2002，25，2：	1
16	Greedy mixture learning for multiple motif discovery in biological sequences 显示文摘	Blekas K Fotiadis D I Likas A	2003	Bioinformatics2003，19，5：	1
17	Automatic Sei- zure Detection Based on Time-Frequency Analysis and Artificial Neural Networks 显示文摘	Tzallas A T Tsipouras M G Fotiadis D I	2007	Computational Intelligence and Neuoscience2007，2007，80：	1
18	Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines 显示文摘	PAPADOPOULOS A FOTIADIS D I LIKAS A	2005	Artificial Intelligence in Medicine2005，34，2：	1
19	A multichannel watershed-based segmentation method for multispectral chromosome classification显示文摘	Karvelis P S Tzallas A T Fotiadis D I	2008	IEEE Transactions on Medical Imaging2008，27，5：	1
20	Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines显示文摘	Papadopoulos A Fotiadis D I Likas A	2004	Artificial Intelligence in Medicine2004，34，2：	1

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